• Asia pacific journal of information systems
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• v.19 no.2
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• pp.73-94
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• 2009

The general aspects for the future warfare shows that the concept of firepower and maneuver centric warfare has been replacing with that of information and knowledge centric warfare. Thus, some developed countries are now trying to establish the information systems to perform intelligent warfare and innovate defense operations. The C4I(Command, Control, Communication, Computers and Intelligence for the Warrior) systems make it possible to do modern and systematic war operations. The basic idea of this study is to investigate how TAM(Technology Acceptance Model) can explain the acceptance behavior in military organizations. Because TAM is inadequate in explaining the acceptance processes forcomplex technologies and strict organizations, a revised research model based upon TAM was developed in order to assess the usage of the C4I system. The purpose of this study is to investigate factors affecting the usage of C4I in the Korean Army. The research model, based upon TAM, was extended through a belief construct such as self-efficacy as one of mediating variables. The self-efficacy has been used as a mediating variable for technology acceptance, and the variable was included in the research model. The external variables were selected on the basis of previous research. The external variables can be classified into following: 1) technological, 2) organizational, and 3) environmental factors on the basis of TOE(Technology-Organization-Environment) framework. The technological factor includes the information quality and the task-technology fitness. The organizational factor includes the influence of senior colleagues. The environmental factor includes the education/train data. The external variables are considered very important for explaining the behavior patterns of information technology or systems. A structured questionnaire was developed and administrated to those who were using the C4I system. Total 329 data were used for statistical data analyses. A confirmatory factor analysis and structured equation model were used as main statistical methods. Model fitness Indexes for measurement and structured models were verified before all 18 hypotheses were tested. This study shows that the perceived usefulness and the self-efficacy played their roles more than the perceived ease of use did in TAM. In military organizations, the perceived usefulness showed its mediating effects between external variables and dependent variable, but the perceived ease of use did not. These results imply that the perceived usefulness can explain the acceptance processes better than the perceived ease of use in the army. The self-efficacy was also used as one of the three mediating variables, and showed its mediating effects in explaining the acceptance processes. Such results also show that the self-efficacy can be selected as one possible belief construct in TAM. The perceived usefulness was influenced by such factors as senior colleagues, the information quality, and the task-technology fitness. The self-efficacy was affected by education/train and task-technology fitness. The actual usage of C4I was influenced not by the perceived ease of use but by the perceived usefulness and selfefficacy. This study suggests the followings: (1) An extended TAM can be applied to such strict organizations as the army; (2) Three mediation variables are included in the research model and tested at real situations; and (3) Several other implications are discussed.

• Journal of the Korean Society for Railway
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• v.12 no.3
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• pp.405-411
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• 2009

Railway signaling system in a rapid transit using the ATC system the approved a speed limit to a train and a part of signaling system in a metro approved a distance which is possible to move. Referring to the way of transmitting train control information, there are the one transmitting it to the on-board system of a train using the direct track, the another transmitting it establishing an instrument, and the other transmitting an instrument by a railway track. The one is the method using the direct track as a conductor for composing the part of the track and attaining the information controlling a train by transmitting a signal to the track. It is used for the high-speed railway and the subway. The method using the track attains information by transmitting it to returned information, and the on-board system of a train attains it by magnetic coupling. Because many reinforcing bars on the concrete slab track are used, interaction between a rail and a reinforcing bar that is not produced on ballast track is made. Due to the interaction, the electric characteristic of rail is changed. In the current paper, we numerically computed the coupling coefficient between the rail and the reinforcing bar based on the concrete slab track throughout the model related to the rail and the reinforcing bar using the concrete slab track that is used in the second interval of the Gyeongbu high-speed railway, and we defined the coupling coefficient not changed in the electric characteristic of rail in the condition that there is no interaction between the rail and the reinforcing bar.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.61-69
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• 2020

This study examined the braking characteristics of a heavy haul freight train with P4a distribution valves applied to domestic high-speed freight trains. A freight train was composed of 50 cars, which is twice the normal operation. A braking test was performed to confirm the characteristics of the braking of a heavy haul. The brake cylinder pressures were measured for emergency and service braking on the 1st, 10th, 20th, 30th, and 50th cars. Because the brake signal is transmitted to the pressure through the braking tube connected to the end of the train, the rear vehicle is braking later than the vehicle ahead. Therefore, it is necessary to predict the brake pressures in all cars in a train to supplement the results of the limited tests and calculate the braking distance. The pressure in each car was determined using empirical models of linear interpolation, stepwise, and exponential models, which provided reliable information. The predictive results of the empirical models were compared with the measured results, and the exponential model was predicted relatively accurately. These results are expected to contribute to the safe operation of heavy haul freight trains and can be used to predict the braking distance and calculate the level of impact between vehicles during braking.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.3
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• pp.293-310
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• 2020

The purpose of this study is to present the most effective smoke exhaust mode by comparing the quantitatively evaluated risks according to the smoke exhaust mode when a train fire occurs in a subway platform. Therefore, applying the typical subway platform as a model, train fire scenarios are developed with the evacuation start time and location of the fire train for each exhaust mode. The fire accident rates (F) are calculated and the number of fatalities (N) was quantitatively estimated by fire analysis and evacuation analysis for each scenario. In addition, the F/N curve compared with the social risk assessment criteria and the following conclusions were obtained. In the event of a train fire at the subway station platform, the evacuation must start up within 600 s in maximum to ensure the evacuees' safety. To secure evacuation safety, it is advantageous to operate the HVAC system of the platform in the air-supply mode at station without TVF. Comparing the F/N curve for each exhaust mode with the social risk criteria, it turned out that the risk significantly exceeds the social risk criteria in case of no mechanical ventilation. As a result, this paper shows that the ventilation mode in which TVF are exhausted and HVAC system is operated in the pressurized mode are the most effective smoke exhaust mode for ensuring evacuation safety.

• Steel and Composite Structures
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• v.39 no.3
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• pp.319-335
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• 2021

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R² = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R² = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.539-546
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• 2016

It is over 12 years since the launch of Korea Train eXpress (KTX) services. Demand for the KTX has been on the increase continuously but few studies have been produced related to this phenomenon. KTX passenger demand has been constantly increasing due to influencing factors such as the expansion of network, rise of oil prices, etc. In this study, our main focus is to verify that there are other types of elements that are causing an increase in KTX demand; our approach looks at changes in social and psychological aspect that have occurred due to the reduction of travel time and cost, as well as the imposition of a five-day workweek. In other words, we considered diffusion theory in the marketing area, which affects product selection and purchasing attitudes, as a key factor that is causing passenger demand to increase. That is to say that it is hypothesized that the demand for travel on the KTX has increased due to the train's utility, which is spread by the diffusion effect Therefore, the Bass diffusion model was applied to explain the dramatic increase in KTX passenger demand. Based on this foundation, it was also discussed how certain marketing strategies that incorporate the diffusion effect should be considered variously for sustainable management of rail transportation, while considering a steady passenger demand.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.541-552
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• 2023

Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using supine and erect abdominal radiography. Materials and Methods: A model that can utilize "pneumoperitoneum" and "non-pneumoperitoneum" classes was developed through knowledge distillation. To train the proposed model with limited training data and weak labels, it was trained using a recently proposed semi-supervised learning method called distillation for self-supervised and self-train learning (DISTL), which leverages the Vision Transformer. The proposed model was first pre-trained with chest radiographs to utilize common knowledge between modalities, fine-tuned, and self-trained on labeled and unlabeled abdominal radiographs. The proposed model was trained using data from supine and erect abdominal radiographs. In total, 191212 chest radiographs (CheXpert data) were used for pre-training, and 5518 labeled and 16671 unlabeled abdominal radiographs were used for fine-tuning and self-supervised learning, respectively. The proposed model was internally validated on 389 abdominal radiographs and externally validated on 475 and 798 abdominal radiographs from the two institutions. We evaluated the performance in diagnosing pneumoperitoneum using the area under the receiver operating characteristic curve (AUC) and compared it with that of radiologists. Results: In the internal validation, the proposed model had an AUC, sensitivity, and specificity of 0.881, 85.4%, and 73.3% and 0.968, 91.1, and 95.0 for supine and erect positions, respectively. In the external validation at the two institutions, the AUCs were 0.835 and 0.852 for the supine position and 0.909 and 0.944 for the erect position. In the reader study, the readers' performances improved with the assistance of the proposed model. Conclusion: The proposed model trained with the DISTL method can accurately detect pneumoperitoneum on abdominal radiography in both the supine and erect positions.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2049-2056
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• 2011

The reinforced-roadbed materials composed of crushed stones are used for preventing vertical deformation and reducing impact load caused by highspeed train. Repeated load application can induce deformation in the reinforced-roadbed layer so that it causes irregularity of track. Thus it is important to understand characteristics of permanent deformation in the reinforced-subbase materials. The characteristics of permanent deformation can be simulated by prediction model that can be obtained by performing repetitive triaxial test. The prediction model of permanent deformation is a key-role in construction of design method of track. The prediction model of permanent deformation is represented in usual as the hyperbolic function with increase of number of load repetition. The prediction model is sensitive to many factors including stress level etc. so that it is important to define parameters of the model as clearly as possible. Various data obtained from repetitive triaxial test and resonant column test using the reinforced-roadbed of crushed stone are utilized to develop a new prediction model based on concept of shear-stress ratio and elastic modulus. The new prediction model of permanent deformation can be adapted for developing design method of track in the future.

• Journal of The Korean Association of Information Education
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• v.16 no.3
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• pp.299-307
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• 2012

Even though there are many models for educational curriculum of giftedness for children, there is little model for educational methodology and curriculum of information science giftedness of children. A curriculum model for information science giftedness of children is proposed on this study. This model's characteristics is a modular integrated curriculum model combined the mathematics, natural science, and information science. Because there is no regular curriculums of information science at elementary school. this model is valided. Also, There is also need to train multiple areas in the field of information science to expose information science giftedness of the children, This model is to minimize the relationship between modules, and to maximize the cohesion in the each module. As for result of statistics analysis for 60 giftedness students during three years, we know the effectiveness of this model.